Descriptive Statistical Summary Using Pandas in Python | Describe for Numeric & Character variables

After knowing metadata information of the given dataframe (which we covered in "Know your pandas dataframe in python" video), the time comes to start diving into the data and that's where it becomes important to know how can you apply the most basic and frequently used descriptive statistical techniques using pandas and get the summary of your data. This video covers: 00:00 - Introduction 03:13 - Getting the number of non-missing values in the column/s 04:22 - Getting the total sum of variable/variables 06:31 - Getting the average/mean value of a variable/variables 08:30 - Getting the spread/standard deviation of data in a variable or variables 09:49 - Getting most frequently used item or mode in a variable or variables 10:28 - Getting the least & most or minimum & maximum value in a variable or variables 12:10 - Finding the cumulative sum of a variable or variables 14:04 - Getting the basic descriptive statistical summary using describe function 16:05 - Getting the basic descriptive statistical summary for character variables using describe function 17:06 - Getting the basic descriptive statistical summary for character & numeric both type of variables using describe function To download the original data which have been used in this video, check out the link given below: https://www.kaggle.com/aungpyaeap/supermarket-sales To get the excel file of exact same data which we have used in the video (i.e. 1000 rows and 12 columns), checkout the below link: https://github.com/LEARNEREA/Matplotlib/blob/main/supermarket_sales_data.xlsx To find the script covered in this video, check out the below link: https://github.com/LEARNEREA/Matplotlib/blob/main/descriptive_statistics.py To learn how to get the metadata information like data types, number rows and columns etc. check out the video using below link: https://youtu.be/6tW7HCoOAi4 #Learnerea #Python #DescriptiveStatistics #DescriptiveSummary #DescriptiveStatisticalSummary #Python #Pythontutorial #Pythononlinetraining #Pythonforbeginners #PythonProgramming #PythonMatplotlib